Pulmonology

Potential for AI as first reader in lung cancer screening.

PURPOSE: To retrospectively assess the agreement between human and automated AI-based readings for low-dose computed tomography (LDCT) outcomes according to LungRADS v1.1 in lung cancer screening (LCS); to test the diagnostic performance of both readings. METHODS: We included 4104 baseline LDCTs from the BioMILD trial. Original readings were retrospectively classified into "negative" (LungRADSv1.1...

An explainable machine learning model predicts 30-day readmission after vertebral augmentation.

Osteoporotic vertebral compression fracture (OVCF) patients face high 30-day readmission risks after vertebral augmentation procedures (VAPs). Using electronic health records (EHRs) of 3,947 OVCF patients who underwent VAPs (2019-2024), we developed an interpretable machine learning model to identify readmission predictors. Eight algorithms were evaluated via 10-fold cross-validation, and XGBoost ...

Emerging options and future strategies in immunotherapy for advanced lung squamous-cell carcinoma.

Advanced-stage lung squamous-cell carcinoma (LUSC) remains a therapeutic challenge. Although immune checkpoint inhibitors (ICIs) have revolutionized L...

Novel growth pattern-specific digital marker of TILs improves stratification of lung adenocarcinoma patients.

Lung adenocarcinoma (LUAD) is one of the most prevalent forms of cancer and continues to be associated with high mortality rates, despite recent advan...

Ultrasound to guide critical decisions: What you need to know.

BACKGROUND: Hypotension in the intensive care unit (ICU) demands rapid diagnosis and intervention, as delays in identifying the etiology of shock dire...

Targetable atrial tachycardias after artificial intelligence-guided ablation of persistent atrial fibrillation.

BACKGROUND: The TAILORED-AF randomized trial demonstrated that artificial intelligence-guided ablation of spatiotemporal dispersion in addition to pul...

Engineering strategies for microbial synthesis, customized modification, and application of hemoglobin.

Hemoglobin is a functional protein with heme as a cofactor, playing a crucial role in transporting oxygen and maintaining nitric oxide metabolic balan...

Deep learning for automated alveolar cleft segmentation and bone graft volume estimation in cone-beam computed tomography imaging: a multicenter study.

OBJECTIVE: To train and validate a deep learning-based diagnostic tool capable of accurately segmenting the alveolar cleft region and automatically es...

Automatic segmentation and CT-based deep learning radiomics nomogram for predicting overall survival in patients with small cell lung cancer: A multicenter cohort study.

BACKGROUND AND OBJECTIVE: Accurate prediction of overall survival (OS) in patients with small cell lung cancer (SCLC) is crucial for personalized trea...

Using Artificial Intelligence to Adjudicate Major Adverse Cardiovascular Events in Clinical Trials.

BACKGROUND: Major adverse cardiovascular events (MACE)-cardiovascular (CV) death, nonfatal myocardial infarction (MI), and nonfatal stroke-are highly ...

Pathologic assessment of resected stage III non-small cell lung cancer after neoadjuvant chemotherapy: identification of additional prognostic factors.

BACKGROUND: Non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemotherapy (NACT) followed by surgery represent an ideal clinical set...

Interpretable forecasting of dissolved oxygen leveraging foundation model for proactive aeration in rural wastewater treatment systems.

Accurate forecasting of dissolved oxygen (DO) is crucial for maintaining biological treatment and minimizing energy consumption in wastewater systems....

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approach to identify individuals at risk for heart failur...

From voxel to treatment response: Rethinking the role of imaging in cystic fibrosis in the era of artificial intelligence.

Deep learning framework for bronchoscopic diagnosis of burn inhalation injury.

Burn inhalation injury (BII) increases mortality and morbidity in burns patients. Accurate bronchoscopic grading, as the gold standard diagnostic moda...

Novel Machine-Learning Models Outperform Noninvasive Tests in Metabolic Dysfunction-Associated Steatohepatitis With Fibrosis.

BACKGROUND & AIMS: Noninvasive tests (NITs) have not yet been systematically evaluated or optimized to detect metabolic dysfunction-associated steatoh...

Artificial intelligence in chronic obstructive pulmonary disease: recent advances in imaging and physiological monitoring.

PURPOSE OF REVIEW: Chronic obstructive pulmonary disease (COPD) is a leading cause of worldwide morbidity and mortality, yet significant barriers in i...

Development and validation of self-management education module of ChestCare app: Empowering healthy behaviours in chronic obstructive pulmonary disease.

ObjectiveIn this mixed-methods study, we aimed to develop a self-management education module within the ChestCare mHealth app, thus enabling patients ...

Medication-based mortality prediction in COPD using machine learning and conventional statistical methods.

BACKGROUND: Predicting mortality in chronic obstructive pulmonary disease (COPD) patients supports clinical decision-making and resource allocation. W...

Multiperspective tumor heterogeneity metrics for preoperative prediction of IASLC grading in clinical stage IA lung adenocarcinomas: A multicenter study.

BACKGROUND AND OBJECTIVE: Accurate preoperative prediction of the International Association for the Study of Lung Cancer (IASLC) grades is crucial for...